dmccreary

Creates interactive educational MicroSims, routing to the best-matched generator - p5.js, Chart.js, Plotly, Mermaid, vis-network, timelines, maps, Venn, causal-loop/feedback-loop diagrams (CLD), concept-classifier sorting quizzes, infographic overlays with callout labels, and Docker Python labs (runnable code blocks). Generates complete MicroSim packages with HTML, JavaScript, CSS, documentation, and metadata.

Generates media for intelligent textbooks - slide decks and presentations (MARP web decks in docs/slides/ or PowerPoint .pptx lecture downloads), illustrated stories and graphic novels, fact-checked infographic posters, freely-licensed chapter images from Wikimedia and government archives, and audio (text-to-speech voiceovers, glossary pronounce buttons via ElevenLabs). Routes to the appropriate media guide.

Installs and configures intelligent-textbook infrastructure - scaffold a brand-new MkDocs Material textbook (init textbook), install any of 40 features (math, mascot, learning graph viewer, Google Analytics GA4, custom 404, kanban board), and generate book metrics. Routes to the appropriate installation guide.

Publishes and promotes a finished intelligent textbook - GitHub README with badges and site statistics, LinkedIn announcement posts, LinkedIn carousel document posts (PPTX/PDF slideshows), and AP-style press releases. Use when announcing a book milestone or updating repository documentation. Routes to the appropriate guide.

Utility tools for MicroSim management including quality validation, screenshot capture, icon management, index page generation, iframe height synchronization, iframe control-visibility testing, visual layout review, and diagram/MicroSim coverage reports across chapters. Routes to the appropriate utility based on the task needed.

Generates detailed chapter content for an intelligent textbook — text, diagrams, MicroSims, and exercises at the appropriate Bloom's level. Use when a chapter's index.md exists with title, summary, and concept list.

Generates a FAQ set for an intelligent textbook from course content, learning graph, and glossary terms. Use after the learning graph and glossary exist and at least 30% of chapters are written.

Designs the chapter structure for an intelligent textbook by analyzing the learning graph and concept dependencies. Use after the learning graph is complete and before generating chapter content.

Generate clear, beginner-friendly circuit and wiring diagrams for microcontroller projects (Raspberry Pi Pico + NeoPixels, push buttons, rotary encoders, sensors, switches, batteries) using the schemdraw Python library, in the Moving Rainbow house style — red power rail across the top, black ground rail across the bottom, amber signal wires, light component blocks, white background, and PNG + SVG output. Use this skill whenever the user wants to create, draw, generate, redraw, or update a circuit diagram, wiring diagram, schematic, hookup figure, "how the parts connect" illustration, or breadboard wiring picture for a kit or microcontroller project — even if they don't mention schemdraw by name. Also use it when adding a wiring figure to a kit's documentation page.

Generate MicroPython programs for the Moving Rainbow LED strip educational project using Raspberry Pi Pico with NeoPixel strips and button controls.

This skill generates Python scripts and shell scripts to control RGB LEDs on the Raspberry Pi 500+ keyboard. Use this skill when the user asks to create keyboard lighting effects, animations, color patterns, notification systems, or any program that controls the Pi 500+ keyboard LEDs. This skill should be used for requests like "turn F1-F12 keys blue", "create a typing speed indicator", or "make an email notification effect".

This skill generates case study entries for intelligent textbook projects from GitHub repositories. Use this skill when adding a new case study to the case studies index page, when the user provides a GitHub repo URL and wants to create a case study card entry. The skill handles repo analysis, thumbnail generation/compression, and markdown entry formatting.

This skill generates case study entries for intelligent textbook projects from GitHub repositories. Use this skill when adding a new case study to the case studies index page, when the user provides a GitHub repo URL and wants to create a case study card entry. The skill handles repo analysis, thumbnail generation/compression, and markdown entry formatting.

Refactoring patterns and best practices for creating maintainable geometry MicroSims using p5.js. Provides guidelines for local coordinate systems, push/pop/translate/scale patterns, mathematical accuracy, and clean code structure.

This skill generates comprehensive diagram and MicroSim reports for the geometry course by analyzing chapter markdown files and creating table and detail reports. Use this skill when working with an intelligent textbook (specifically geometry-course) that needs updated visualization of all diagrams and MicroSims across chapters, including their status, difficulty, Bloom's Taxonomy levels, and UI complexity.

Given a title and description of textbook suggest an existing mascot design or generate a new mascot design.

Scan sibling book/course projects under /Users/dan/Documents/ws/ for new mascot directories and import any not yet present in this book-mascots repo. Use this skill whenever the user says things like "update the mascots", "check for new mascots", "import mascots", "sync mascots from the other books", "are there any new mascots to bring in", or otherwise asks to refresh this gallery from sibling projects. Copies pose PNGs and the prompt file into docs/mascots/<slug>/, regenerates per-mascot index pages, rewrites docs/list-mascots.md, updates the Mascots nav section in mkdocs.yml, and prints a summary report (new mascots added, total count, anything skipped).

Generates RLC circuit diagrams from text descriptions using Schemdraw. Use this skill when the user wants to create circuit drawings for educational purposes, particularly for AC/DC circuits with resistors, capacitors, inductors, and power sources.

Generates a comprehensive learning graph from a course description, including 200 concepts with dependencies, taxonomy categorization, and quality validation reports. Use this when the user wants to create a structured knowledge graph for educational content.